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    <title>Environmental Data Abstraction Library (EDAL): Core data types</title>
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      <h1>Overview</h1>
      <p>This module defines core data types - mostly as implementation-free interfaces -
      that are used in EDAL.  The data types represent different kinds of environmental
      information, including numerical model output, satellite observations and
      in situ data.</p>

      <h1>Rationale</h1>
      <p>The aims of these type definitions are:</p>
      <ul>
          <li>to correctly define types that represent information that is typically
              used in GIS-like data visualization and intercomparison applications;</li>
          <li>to help to form a bridge between the GIS world and that of multidimensional
              environmental data (such as may typically be encoded in NetCDF files);</li>
          <li>to have minimal dependencies on third-party libraries, allowing use
              in a number of different environments, including those that do not
              implement the full Java APIs (e.g. Google App Engine, Google Web Toolkit,
              embedded devices;</li>
          <li>to adopt and apply standards where possible, but also to keep the API
              "clean" and easy to use.</li>
      </ul>

      <h1>Related work</h1>
      <p>The Climate and Forecast (CF) metadata standard defines how to encode
         environmental data in NetCDF files.  Although focused mostly on gridded
         data, CF is now encompassing other data types.  EDAL attempts to allow
         (almost) all of the CF metadata to be expressed as convenient Java APIs.</p>
      <p>The Java NetCDF libraries provide a pure-Java interface to NetCDF and other files,
         with some abstractions of data types (the Common Data Model) that are similar to those of EDAL.
         An EDAL module provides a wrapper around the CDM, providing a more GIS-friendly view.</p>
      <p>GeoAPI defines Java interfaces that express certain OGC and ISO standards.
         EDAL follows a similar approach but is more tailored to multidimensional
         environmental data, and is less comprehensive and complex than GeoAPI.</p>


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